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LegalMind: An Intelligent Solution for Legal Document Analysis with User-Centric UI and AI-Driven Capabilities in Mobile Devices

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dc.contributor.authorWasi, Azmine Toushik-
dc.contributor.authorIslam, Mst Rafia-
dc.contributor.authorRahman, Abdur-
dc.contributor.authorYeasmin, Tawfia-
dc.contributor.authorAgarwal, Amit-
dc.contributor.authorPatel, Hitesh Laxmichand-
dc.contributor.authorRafi, Taki Hasan-
dc.contributor.authorChae, Dong-Kyu-
dc.date.accessioned2026-03-19T00:30:34Z-
dc.date.available2026-03-19T00:30:34Z-
dc.date.issued2025-10-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/211359-
dc.description.abstractNavigating legal documents is challenging due to their complexity, jargon, and interconnected entities like names, dates, and provisions, leading to inefficiencies and critical oversights. With the growing reliance on mobile devices, there is an increasing demand for tools that enable efficient and accessible legal document analysis on-the-go. To address these issues, we introduce LegalMind, a mobile app that revolutionizes legal document analysis by integrating key features: Automatic Entity Mapping for quick identification of essential details, Intelligent Question Answering for context-aware responses, and Multi-document Analysis for comprehensive comparison. Designed with a user-centric UI, LegalMind streamlines information retrieval, reduces manual effort, and enhances decision-making for legal professionals. The intuitive UI allows users to easily navigate complex legal content on mobile devices. Our user study confirmed that LegalMind improves efficiency and accessibility, thus showing its ability to transform legal workflows by bridging the gap between complex legal challenges and AI-driven solutions while maintaining a seamless, accessible UI.-
dc.format.extent5-
dc.language영어-
dc.language.isoENG-
dc.publisherAssociation for Computing Machinery-
dc.titleLegalMind: An Intelligent Solution for Legal Document Analysis with User-Centric UI and AI-Driven Capabilities in Mobile Devices-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1145/3715070.3749262-
dc.identifier.scopusid2-s2.0-105031874263-
dc.identifier.bibliographicCitationProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp 410 - 414-
dc.citation.titleProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW-
dc.citation.startPage410-
dc.citation.endPage414-
dc.type.docTypeConference paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusAutomatic identification-
dc.subject.keywordPlusDecision making-
dc.subject.keywordPlusHuman engineering-
dc.subject.keywordPlusInformation retrieval-
dc.subject.keywordPlusInformation retrieval systems-
dc.subject.keywordPlusInformation systems-
dc.subject.keywordPlusLaws and legislation-
dc.subject.keywordPlusMobile applications-
dc.subject.keywordPlusMobile computing-
dc.subject.keywordPlusQuestion answering-
dc.subject.keywordPlusUser interfaces-
dc.subject.keywordAuthorAI-assisted legal workflow-
dc.subject.keywordAuthorEntity mapping-
dc.subject.keywordAuthorLegal document analysis-
dc.subject.keywordAuthorMobile LegalTech-
dc.subject.keywordAuthorQuestion answering-
dc.identifier.urlhttps://dl.acm.org/doi/10.1145/3715070.3749262-
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